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WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling
[article]
2020
arXiv
pre-print
To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid autoencoding inference (WHAI) for deep latent Dirichlet allocation, which infers posterior samples via a hybrid of stochastic-gradient MCMC and autoencoding variational Bayes. The generative network of WHAI has a hierarchy of gamma distributions, while the inference network of WHAI is a Weibull upward-downward
arXiv:1803.01328v2
fatcat:6bvohpvnwjaibocikfjn32bu7e